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problems of our time, perhaps of all time.

“The cosmological questions of where everything in theuniverse comes from and develops as matter and energy.The biological questions of the origin and development oflife and the nature of intelligence, the awe-inspiring infor-mation-processing abilities that allow us to perceive, think,wonder, and raise such questions.”

Feigenbaum, one of the forefathers of AI, has manyopinions and perceptions of AI and has seen where AI hascome from and where it is going.

“Over time AI has matured, ‘professionalized,’ ex-panded to tens of thousands of researchers and in theprocess managed to lose many of its visionaries—likeSimon and Newell—and much of its vision. It has becomewhat Thomas Kuhn called “routine science,” building itsscience incrementally, journal article by journal article,often faddishly,” Feigenbaum says. “It seems little moti-vated by the long-term vectors laid out by Turing, Simon,Minsky, McCarthy, Bledsoe, Reddy, and me, to name afew. As a field, it seems to prefer not to pursue the ‘ultra-intelligent’ computer, or even what McCarthy has called‘human-level AI.’

“It prefers proofs of the computational complexity of anew method, rather than a risky but brilliant adventureinto a new space of possibilities. But this is not true of allof AI,” Feigenbaum continues. “Some AI scientists arestill great innovators. I am very optimistic.”

Expert systemsFeigenbaum made his name in expert systems. He

invented the first expert system in 1967—an AI program thatdetermined the molecular structure of chemical compounds.

“Early AI researchers, of which I was one, were moti-vated by two dreams: artificial intelligence and computersimulation of cognitive processes. The former was essen-tially an ‘engineering dream,’ and is summed up in the

words once used in the title of an article by I.J. Good,‘Toward the Ultra-Intelligent Computer.’The latter was a‘psychology’dream, in which the underpinnings of theory incognitive psychology would be reworked to be information-processing psychology,” Feigenbaum says. “The psychol-ogy dream has been largely achieved. The engineeringdream has been partly achieved by expert systems.”

Two of the earliest expert systems, Dendral and Mycin,“achieved performance levels in their behavior—in nar-row areas of expertise—that were equal to the perfor-mance levels of the best human expert practitioners,”Feigenbaum says.

Tens of thousands of expert systems have been built,and today they are usually embedded within larger sys-tems—in firewalls, in configuration systems, and in man-ufacturing scheduling systems.

A rtificial Intelligence holds the keys to different

things to different researchers. For Ed Feigenbaum,

it holds “the keys to one of the three supreme scientific

AI Holds the Keys

Scott L. Andresen

“Because the expert system research sci-entist was necessarily working on real prob-lems with real human experts who had realexpertise, the confrontation with the realworld brought forth new research ideas,entirely new methods that brought aboutbig shifts in the research of the AI commu-nity. The most obvious examples were inknowledge representation and machinelearning,” Feigenbaum says. “The key com-ponent of an expert system is its knowledgebase. The knowledge engineers could notuse knowledge representations that weremerely theoretically interesting. You canthink of each expert system that was built asan experiment on the question: where doesthe power of an expert system come from?The experiments found that in almost allcases, the power to solve complex problemsat human levels of expertise comes from theknowledge base. In a much-quoted articlein 1977, [Ira] Goldstein and [Seymour]Papert, of MIT, noted in the AI field a ‘shiftto the knowledge-based paradigm.’”

Feigenbaum also says that in a 1984 arti-cle in the Journal of Artificial Intelligence,Allan Newell said that the most importantdevelopment of AI over the last decade wasthe emergence of expert systems.

“The power of AI systems is almostalways the power of the knowledge in thesystem’s knowledge base, not the power ofits inference procedures or problem-solving

frameworks. I have called this the knowl-edge principle,” Feigenbaum says. “Toachieve the behavior that Turing was think-ing about when he proposed his famous testin 1950 will require a huge knowledge basethat codifies human experience. My formerstudent and close friend, Douglas Lenat,has been working on building such a knowl-edge base using the talents of dozens ofskilled knowledge engineers (the CYC project). But their knowledge base is stillfar too small to do the job. What might beneeded is the volunteer effort of tens ofthousands, perhaps hundreds of thousands,of individuals who use semantic markuplanguages to mark up Web pages for seman-tic content. They will be guided by ontolo-gies again built by hundreds of people(including those donated to the AI commu-nity by Lenat). Other programs will also beneeded to gather, organize, and index theknowledge scraped from the mark-ups.

“Probably the reason that we have onlyexpert AI programs and not general-pur-pose AI programs—like the Turing-test—isthat the job I have just described is so diffi-cult, and it is not something computer sci-entists like to do. Computer scientists likealgorithms and process, not content. Con-tent is what other people do.”

AI beginningsFeigenbaum studied under Herb A.

Simon at Carnegie Mellon in the mid1950s and was present at the birth of thefirst heuristic program, the Logic Theorist.“I was inspired by the vision and technicalbrilliance of Simon—initially—and Newell,and simply stayed at Carnegie for my grad-uate work. I did my thesis under Simon onthe psychology side of AI and left Carnegiein 1959,” Feigenbaum says. “But the workon DENDRAL that led to the invention ofthe expert systems concept did not beginuntil 1965 when I moved from Berkeley toStanford and began my collaboration withJoshua Lederberg.”

From those early beginnings at CarnegieMellon, to his research at Stanford, to hiswork as the chief scientist for the Air Forcein the mid 1990s, Feigenbaum has seen thepromise of AI grow. “I thought we wouldbe further along in the construction of largeknowledge bases, and hence further alongtoward human-level AI. I [also] thought wewould be further along in the building ofknowledge acquisition and knowledge dis-covery software so that the task of buildingthose knowledge bases would be at leastpartially automated by now. Lenat and Idiscussed the ‘bootstrapping’ of knowl-edge, using knowledge in a paper that wewrote for IJCAI 1987, called ‘On theThreshold of Knowledge,’” Feigenbaumsays. “But the bootstrapping has not hap-pened yet.”

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Ed Feigenbaum was chairman of the Computer Science Department and director of the Computer Center at Stanford University.Until 1992, Dr. Feigenbaum was coprincipal investigator of the national computer facility for applications of artificial intelligence tomedicine and biology known as the SUMEX-AIM facility, established by the National Institute of Heath at Stanford University. He isthe past president of the American Association for Artificial Intelligence. He has served on the National Science Foundation Com-puter Science Advisory Board, an ARPA study committee for Information Science and Technology; and the National Research Coun-cil’s Computer Science and Technology Board. He has been a member of the Board of Regents of the National Library of Medicine.

He was the coeditor of The Handbook of Artificial Intelligence and Computers and Thought. He is coauthor of Applications ofArtificial Intelligence in Organic Chemistry: The DENDRAL Program and was the founding editor of the McGraw-Hill Computer Sci-ence Series. He is coauthor with Pamela McCorduck of The Fifth Generation: Artificial Intelligence and Japan’s Computer Challengeto the World. He is also coauthor with Penny Nii and Pamela McCorduck of The Rise of the Expert Company, a book about corpo-rate successes in the use of expert systems.

He is a cofounder of three start-up firms in applied artificial intelligence—IntelliCorp, Teknowledge and Design Power—andserved as a member of the board of directors of IntelliCorp and Design Power. He also was a member of the board of directors ofSperry Corporation prior to its merger with Burroughs. He is a member of the Advisory Council of the Kansai Silicon Valley Ven-ture Forum.

He was elected to the National Academy of Engineering in 1986. In the same year, he was elected to the Productivity Hall of Fameof the Republic of Singapore. He is an elected fellow of the AAAI. He was elected to the American Academy of Arts and Sciences in1991. He is the first recipient of the Feigenbaum Medal, an award established in his honor by the World Congress of Expert Systems.He was elected fellow to the American Institute of Medical and Biological Engineering in January 1994. He was received the 1994ACM Turing Award. He was named Kumagai Professor of Computer Science at Stanford University in 1995. He received the US AirForce Exceptional Civilian Service Award in 1997. He received his BS and PhD from Carnegie Mellon University.

Achievements